ResNet50_on_Cifar_100_Without_Transfer_Learning
I am a young person who is curious about image classification. I have an average knowledge and an average computer. I thought the cifar 100 data for image classification was challenging for me. It was a data containing 100 classes from 32x32 and 100 images. I chose resnet as the model due to the low number of data and gradient vanishing problem. I worked with google colab because my computer is not enough (thank you Google) Since I used the free version, I could only run Resnet50. I tried to stick to the original Resnet article. But I made it myself in changes. I have tried many hyper parameters. I found the parameters that gave the best results as soon as possible as fast as I could. I'm a young man who likes to push his luck. that is all
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Datasets
Task | Dataset | Model | Metric Name | Metric Value | Global Rank | Benchmark |
---|---|---|---|---|---|---|
Image Classification | CIFAR-100 | ResNet50 Without Transfer Learning | Percentage correct | 67.060 | # 176 |